At Henkel, you can be a game changer and craft your career. Unleash your entrepreneurial spirit by bringing your ideas to life within a global team. Our leading brands and technologies, along with our high-performing businesses will provide you with countless opportunities to develop your skills and explore new paths. Your career at Henkel will contribute to a more sustainable future, while you grow within our vibrant, diverse culture of trust and belonging. If you're up for challenging the status quo, join our team of pioneers and make your mark on the future with us.
Do you dare to make an impact?
YOUR ROLE
- Act as lead analytics engineer designing & developing analytical solutions and datasets for end users.
- Data modeling experience in a way that empowers end users.
- Organize and transform data in a meaningful way and provide additional context so that it is ready for analysis.
- Design, develop and use tools, algorithms, and processes for data analysis and data visualization to generate reports to be used in decision making of end users.
- Write production-quality ELT code with an eye towards performance and maintainability.
- Live software engineering best practices (e.g., building testing suites and CI pipelines).
- Design, build, and enhance tools and techniques for our DataOps approach such as automatic code generation, automatic data validation and maintenance of development, test and production environments.
- As an Architect, be part of a team of data professionals in the Data & Analytics department, guide the team with your expertise and extend and deepen your knowledge by strong collaboration within the team.
- Actively participate in cross-functional teams using agile methods to deliver high quality data products at a fast pace.
- Ensure documentation related to datasets and analysis is maintained as well as ensure that everyone on the data team uses the same language and definitions.
- Collaborate with our platform team to discover opportunities to improve our systems, enterprises, and processes to have high-quality data.